[em500]

Time series are numbers measured or aggregated at some consecutive times or days. It's a data type with a specific structure, like a set, a vector or a matrix: what's inside varies a lot and depends on the specific application (e.g. daily temperature, rainfall, stock prices, items sold, water level in a river, corona infections).

Prophet is a Python library that implements a specific type of extrapolation model to predict the future: i.e. you input a few months/years of historical daily sales figures, it tries to detect trends and recurring patters, and it outputs predictions of future daily sales. It's currently one of the most popular approaches, probably because it's pretty easy to use and a good fit for many time series in commercial companies. The article shows a lot of of examples of time series where the approach does not work well.

If the layperson doesn't have to produce forecasts for their job, (s)he probably has little use for Prophet (or other statistical forecasting models).